Palavras-chave: hortaliça secagem convectiva Acmella oleracea A B S T R A C TThe aim of this paper was to analyze the drying kinetics, test the Akaike information criterion (AIC) and Schwarz's Bayesian information criterion (BIC) in the selection of models, determine the effective diffusivity and activation energy of the crushed mass of 'jambu' leaves for different conditions of temperature and layer thicknesses. The experiment was carried out at the Food Laboratory of the Brazilian Agricultural Research Corporation (Embrapa) in Macapá-AP. Drying was carried out in air circulation oven with speed of 1.0 m s -1 at various temperatures (60, 70 and 80 ºC) and layer thicknesses (0.005 and 0.010 m). The experimental data were fitted to 11 mathematical models. Coefficient of determination (R²), mean relative error (P), mean estimated error (SE), Chi-square test (χ²), AIC and BIC were the selection criteria for the models. For the effective diffusivity, the Fick's diffusion model was used considering the flat plate geometry. It was found that Midilli and Logarithmic models showed the best fit to the experimental data of drying kinetics. Effective diffusion coefficient increases with increment in the thickness of the material and with the temperature elevation. Activation energy of the material was of 16.61 kJ mol -1 for the thickness of 0.005 m, and 16.97 kJ mol -1 for the thickness of 0.010 m. AIC and BIC can be additionally included to select models of drying.Cinética de secagem da massa triturada de jambu: Difusividade efetiva e energia de ativação R E S U M O Objetivou-se com o presente trabalho analisar a cinética de secagem, testar os critérios da informação de Akaike (AIC) e informação Bayesiano de Schwarz (BIC) para seleção dos modelos, determinar a difusividade efetiva e a energia de ativação de massa triturada de folhas de jambu para diferentes condições de temperatura e espessuras de camada. O experimento foi desenvolvido no Laboratório de Alimentos da Empresa Brasileira de Pesquisa Agropecuária (Embrapa), em Macapá -AP. A secagem foi realizada em estufa de circulação de ar com velocidade de 1,0 m s -1 em diferentes temperaturas (60, 70 e 80 ºC) e espessuras da camada (0,005 e 0,010 m). Aos dados experimentais foram ajustados onze modelos matemáticos. O coeficiente de determinação (R²), erro médio relativo (P), erro médio estimado (SE), teste de Qui-quadrado (χ²), AIC e BIC, foram os critérios de seleção dos modelos. Para a difusividade efetiva utilizou-se o modelo difusivo de Fick para a forma geométrica de placa plana. Constatou-se que os modelos de Midilli e Logaritmo melhor se ajustam aos dados experimentais da cinética de secagem. O coeficiente de difusão efetivo aumentou com o incremento da espessura da camada de material e com a elevação da temperatura. A energia de ativação do material foi de 16,61 kJ mol -1 para a espessura de 0,005 m e de 16,97 kJ mol -1 para a espessura de 0,010 m. Os critérios de AIC e BIC podem ser incluídos adicionalmente para seleção de modelos de secagem.
When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.
The aim of this research communication was to identify chromosome regions and genes that could be related to milk yield (MY), milk fat (%F) and protein percentage (%P) in Brazilian buffalo cows using information from genotyped and non-genotyped animals. We used the 90 K Axiom® Buffalo Genotyping array. A repeatability model was used. An iterative process was performed to calculate the weights of markers as a function of the squared effects of Single Nucleotide Polymorphism (SNP) and allele frequencies. The 10 SNPs with the largest effects for MY, %F and %P were studied and they explained 7·48, 9·94 and 6·56% of the genetic variance, respectively. These regions harbor genes with biological functions that could be related to the traits analyzed. The identification of such regions and genes will contribute to a better understanding of their influence on milk production and milk quality traits of buffaloes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.